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Chengpeng Wang

7 accepted papers

2025

CoRe: Benchmarking LLMs’ Code Reasoning Capabilities through Static Analysis Tasks

NeurIPS 2025spotlight

Large language models (LLMs) have been widely adopted across diverse domains of software engineering, such as code generation, program repair, and vulnerability detection. These applications require understanding beyond surface-level code patterns: value propagation, control flow, and interdependenc…

Cited by 0SourceScholar
2025

QCS:Feature Refining from Quadruplet Cross Similarity for Facial Expression Recognition

AAAI 2025technical

Facial expression recognition faces challenges where labeled significant features in datasets are mixed with unlabeled redundant ones. In this paper, we introduce Cross Similarity Attention (CSA) to mine richer intrinsic information from image pairs, overcoming a limitation when the Scaled Dot-Produ…

2025

RepoAudit: An Autonomous LLM-Agent for Repository-Level Code Auditing

ICML 2025poster

Code auditing is the process of reviewing code with the aim of identifying bugs. Large Language Models (LLMs) have demonstrated promising capabilities for this task without requiring compilation, while also supporting user-friendly customization. However, auditing a code repository with LLMs poses s…

2024

Conversational Drug Editing Using Retrieval and Domain Feedback

ICLR 2024poster

Recent advancements in conversational large language models (LLMs), such as ChatGPT, have demonstrated remarkable promise in various domains, including drug discovery. However, existing works mainly focus on investigating the capabilities of conversational LLMs on chemical reactions and retrosynthes…

Cited by 22SourcePDFScholar
2024

LLMDFA: Analyzing Dataflow in Code with Large Language Models

NeurIPS 2024poster

Dataflow analysis is a fundamental code analysis technique that identifies dependencies between program values. Traditional approaches typically necessitate successful compilation and expert customization, hindering their applicability and usability for analyzing uncompilable programs with evolving…

2024

Sanitizing Large Language Models in Bug Detection with Data-Flow

EMNLP 2024finding

Large language models (LLMs) show potential in code reasoning tasks, facilitating the customization of detecting bugs in software development. However, the hallucination effect can significantly compromise the reliability of bug reports. This work formulates a new schema of bug detection and present…